Determination of the Optimal Reference Signal Frequency in the Task of Power Spectrum Pattern Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F22%3A43968914" target="_blank" >RIV/49777513:23220/22:43968914 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9814106" target="_blank" >https://ieeexplore.ieee.org/document/9814106</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE54603.2022.9814106" target="_blank" >10.1109/EPE54603.2022.9814106</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Determination of the Optimal Reference Signal Frequency in the Task of Power Spectrum Pattern Classification

Popis výsledku v původním jazyce

This article describes the results of an experiment in which a reference signal with its subsequent processing is used to obtain information on the degree of cable insulation degradation. A one-dimensional convolutional neural network is used for signal classification. The reference signal was tested with two methods of insulation degradation, thermal and electrical. The signal was preprocessed to obtain its power spectrum density. After that the obtained result was sent to the input of the neural network. Based on the learning and validation curves and the confusion classification matrices, the optimal frequencies of the reference signal were found.

Název v anglickém jazyce

Determination of the Optimal Reference Signal Frequency in the Task of Power Spectrum Pattern Classification

Popis výsledku anglicky

This article describes the results of an experiment in which a reference signal with its subsequent processing is used to obtain information on the degree of cable insulation degradation. A one-dimensional convolutional neural network is used for signal classification. The reference signal was tested with two methods of insulation degradation, thermal and electrical. The signal was preprocessed to obtain its power spectrum density. After that the obtained result was sent to the input of the neural network. Based on the learning and validation curves and the confusion classification matrices, the optimal frequencies of the reference signal were found.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2022 22nd International Scientific Conference on Electric Power Engineering (EPE 2022)

ISBN

978-1-66541-056-4

ISSN

—

e-ISSN

2376-5631

Počet stran výsledku

4

Strana od-do

1-4

Název nakladatele

VSB - Technical University of Ostrava

Místo vydání

Ostrava

Místo konání akce

Kouty nad Desnou, Czech Republic

Datum konání akce

8. 6. 2022

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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